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Audio-SpectraCLI

Aditya Seth

Aditya Seth

Kolkata, West Bengal

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Audio Spectrum Visualization is a Python project that visualizes real-time audio input as a spectrum using Fast Fourier Transform (FFT). It provides an interactive and dynamic interface for users to start the visualization and exit the program. ...learn more

Project status: Published/In Market

Graphics and Media

Code Samples [1]Links [1]

Overview / Usage

Audio Spectrum Visualization is a Python project that visualizes real-time audio input as a spectrum using Fast Fourier Transform (FFT). It provides an interactive and dynamic interface for users to start the visualization and exit the program.

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Installation & Usage (Using PIP)

  1. Install using pip

    pip install Audio-SpectraCLI

  2. Import and use modules

  • Create a Python file.

  • You can use Example.py as a reference or use the following code :

    from Audio_SpectraCLI import AudioSpectrumVisualizer
    from PyQt5.QtWidgets import QApplication

Creating an instance of AudioSpectrumVisualizer with custom parameters

app = QApplication([])
audio_visualizer = AudioSpectrumVisualizer(
duration=5, fs=22050, block_size=1024, frequency_range=(1000, 5000), color='red')

Starting the audio spectrum visualization

audio_visualizer.show()
app.exec_()

Once you have activated the audio_visualizer instance, feel free to use it wherever in the program. It consists of several parameters (which gives more control to the user), so make sure to configure and add those before using it in your code. Also, the user can modify (wrt v4.0) the Duration (in seconds), Sampling Rate (in Hz), and Block Size.

Methodology / Approach

Current Features (with respect to 4.0)
  • Real-time visualization of Fast Fourier Transform (FFT) spectrum of audio input.
  • Support for adjusting parameters such as duration, sampling rate, and block size.
  • Seamless integration with SoundDevice for audio input capture.
  • Customizable Frequency Range: Allow users to specify the frequency range to display in the spectrum.
  • Color Customization: Provide options for users to customize the colors used in the spectrum visualization.
  • Added PyQt5 modules and a Gaussian filter that enables user input for Duration (in seconds), Sampling Rate (in Hz), Block Size, and also smoothens the output.
  • Much more dynamic and user-controlled interface.

Technologies Used

Python

Repository

https://pypi.org/project/Audio-SpectraCLI/

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